1. Field of the invention
The present invention relates to a method for the identification of a substance in a sample as well as to a software product, containing a software suitable for executing such a method.
2. Description of Related Art
In the field of nuclear magnetic resonance spectroscopy (NMR spectroscopy) the problem has existed for decades that it is not possible to perform an automatic identification of substances contained in a sample with the help of a measured NMR spectrum. Rather, even today NMR spectra still have to be evaluated with great effort by hand in order to be able to identify the substances measured by means of NMR spectroscopy. The success of the identification here depends significantly on the technical expertise of the person performing the manual substance identification. Moreover, the complexity of the composition of the sample which is measured by NMR spectroscopy is also important. In this way, the individual components of a complexly composited sample can generally not be unequivocally, quickly and simply identified with the help of a joint NMR spectrum.
Protons and other NMR-active nuclei, such as for example 15N or 13C, basically produce a defined NMR signal in a defined chemical environment (that is in a specific molecular group of a molecule). Thus, each substance has an individual NMR fingerprint. However, these NMR fingerprints strongly vary depending on the pH value, the temperature, the field strength, the salt concentration and many other parameters. Moreover, the individual NMR fingerprints of different substances contained in a sample often overlap to form complex patterns, from which the individual NMR fingerprints can no longer be readily isolated.
As a result, it has hitherto not been possible to take into account all these factors when it comes to the complex compositions of many substances or to store the various influences of the aforementioned parameters on the individual substances in a database. Because for this purpose extensive series of measurements with various pH values, temperatures, salt concentrations and other parameters would have to be measured for each individual substance. Moreover, it would have to be taken into account that the behaviour of a substance can change depending on the presence of other substances.
DE 10 2010 038 014 A1 describes a method for characterizing a sample comprising the following steps: providing at least one analysis result having a plurality of values, wherein the analysis result was generated by the analysis of a sample by at least one analysis method; determining the value of at least one mathematic relation between at least two values of the plurality of values; generating a characterizing signature of the sample on the basis of the value of the at least one mathematic relation. Thus, this method is directed to characterize a sample—i.e. a complex mixture of different substances—as such. In doing so, it is not relevant to identify the individual substances contained in the sample this—explicitly stated on several passages of DE 10 2010 038 014 A1.
EP 2 161 587 A1 describes a method for automatic analysis of NMR spectra that makes use of a parameter-free interpretation system imitating human logic. This method extracts information from an NMR spectrum in a similar manner like human experts would do this. Thereby, different expert systems are combined which provide distinct NMR spectral features as well as features of a proposed chemical structure. After several iterative method cycles a list of probability weighted hypotheses is generated.
Vu et al.: “An integrated workflow for robust alignment and simplified quantitative analysis of NMR spectrometry data”, BMC Bioinformatics 2011, 12: 405 describe a classical adaptation method for spectra during which a reference spectrum is adapted onto a sample spectrum by modification. In doing so, an algorithm is used which is based on a hierarchical cluster-based peak assignment. This method is strongly dependent on the measurement conditions under which the NMR sample spectrum and the NMR reference spectrum have been recorded.